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A hybrid NHPSO-JTVAC-SVM model for the prediction of production lead time
Haoyu Zhu,Jong Hun Woo,Youngmin Kim 대한산업공학회 2021 대한산업공학회 춘계학술대회논문집 Vol.2021 No.6
In the shipbuilding industry, there exist respective lead time for each production process, that is, the duration between start and finish time. Lead time is necessary data for realizing high-efficiency production planning and systematic production management. Therefore, the accuracy of the lead-time has to be secured. But, the traditional method of lead time management was not a scientific one because it just referenced the past record. This paper proposes the NHPSO–JTVAC-SVM regression model to improve the prediction accuracy of lead time by combining the advanced particle swarm algorithm (PSO) and support vector machine (SVM). Moreover, this paper compares the prediction results with the standard SVM, NHPSO–JTVAC-SVM and other machine learning algorithms. The result demonstrates that the NHPSO–JTVAC-SVM model is feasible to predict the lead time in shipbuilding. The prediction performance is also better than the standard SVM or other machine learning algorithms.
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Ma Chao,Zhu Haoyu,Liang Shikai,Chang Yuzhou,Mo Dapeng,Jiang Chuhan,Zhang Yupeng 대한영상의학회 2024 Korean Journal of Radiology Vol.25 No.1
Objective: Idiopathic intracranial hypertension (IIH) is a condition of unknown etiology associated with venous sinus stenosis. This study aimed to develop a magnetic resonance venography (MRV)-based radiomics model for predicting a high trans-stenotic pressure gradient (TPG) in IIH patients diagnosed with venous sinus stenosis. Materials and Methods: This retrospective study included 105 IIH patients (median age [interquartile range], 35 years [27– 42 years]; female:male, 82:23) who underwent MRV and catheter venography complemented by venous manometry. Contrast enhanced-MRV was conducted under 1.5 Tesla system, and the images were reconstructed using a standard algorithm. Shape features were derived from MRV images via the PyRadiomics package and selected by utilizing the least absolute shrinkage and selection operator (LASSO) method. A radiomics score for predicting high TPG (≥ 8 mmHg) in IIH patients was formulated using multivariable logistic regression; its discrimination performance was assessed using the area under the receiver operating characteristic curve (AUROC). A nomogram was constructed by incorporating the radiomics scores and clinical features. Results: Data from 105 patients were randomly divided into two distinct datasets for model training (n = 73; 50 and 23 with and without high TPG, respectively) and testing (n = 32; 22 and 10 with and without high TPG, respectively). Three informative shape features were identified in the training datasets: least axis length, sphericity, and maximum three-dimensional diameter. The radiomics score for predicting high TPG in IIH patients demonstrated an AUROC of 0.906 (95% confidence interval, 0.836– 0.976) in the training dataset and 0.877 (95% confidence interval, 0.755–0.999) in the test dataset. The nomogram showed good calibration. Conclusion: Our study presents the feasibility of a novel model for predicting high TPG in IIH patients using radiomics analysis of noninvasive MRV-based shape features. This information may aid clinicians in identifying patients who may benefit from stenting.
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조선 생산 공정 데이터의 관리 효율화를 위한 네트워크 구조화 및 분석
우종훈,유상현,윤희창,조영인,하오유주(Haoyu Zhu) 대한산업공학회 2020 대한산업공학회 추계학술대회논문집 Vol.2020 No.11
전체 생산 프로세스를 이루는 각 단위공정과 공정 사이의 선후관계 데이터의 저장 및 관리에 있어 완전성과 무결성을 유지하는 것은 효율적인 생산 계획 및 통제를 위한 전제 조건에 해당한다. 조선 생산 공정의 경우 개별 단위공정의 방대한 양과 종류에도 불구하고 Relational DB 관리 형태의 비효율성으로 인해 통합적인 관리의 미흡함이 발생하고 있다. 본 연구에서는 한 개의 호선 공정에 대해 개별적으로 나뉘어 있던 전체 단위 공정을 선후관계에 따라 연결하여 AON(Activity-On-Node) 네트워크로 모델링하였다. 또한 이렇게 생성된 공정 데이터 네트워크는 일반적인 유향그래프(Directed Graph)의 특성을 가지기 때문에 Network Science 및 Graph Theory 분야에서 도출된 알고리즘의 적용이 가능해진다. 본 연구에서는 해당 알고리즘들을 이용한 분석을 실시하고 그 결과가 생산 계획 및 통제라는 맥락에서 유의미한 정보를 제공할 수 있는지에 대한 연구를 수행하였다.
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Study of Fire Resistance Performance of Stiffened Welded Hollow Spherical Joint Under Axial Tension
Xiaobin Qiu,Tao Chen,Bingsheng Huang,Jingrui Zhu,Zhen Zhang,Haoyu Song 한국강구조학회 2023 International Journal of Steel Structures Vol.23 No.2
To study the fire resistance performance of stiffened welded hollow spherical joints under axial tension, two specimens with load ratios of 0.4 and 0.6 were subjected. The temperature distribution, failure mode, and fire resistance performance of stiffened welded hollow spherical joints under axial tension were obtained. The test results show that the failure mode of the joint was a pull-out failure. During the heating process, the closer to the spherical equator, the higher the spherical temperature, and the temperature of the sphere at the stiffener is lower than that of the sphere at the non-stiffener. The load ratio has a great influence on the refractory performance of the stiffened welded hollow sphere joint. When the load ratio of the specimen is reduced from 0.60 to 0.40, the fire resistance time of the specimen increases by 4.47 min, and the critical temperature increases by 21.3 °C. According to the European Code, the finite element model for the stiffened welded hollow spherical joints is established. The effect law of various influencing factors on the fire resistance performance of stiffened welded hollow spherical joints is studied. The research results show that reducing the load ratio and increasing the thickness of the sphere can significantly improve the fire resistance performance of the joint. The calculation formula of the critical temperature of steel members in the current standard not suitable for the calculation of the critical temperature of the welded hollow spherical joint. The critical temperature values with different load ratios recommended by the current standard were relatively more conservative. Taking the ambient temperature as the fire resistance temperature, the finite element analysis results were fitted, and the formula for calculating the fire resistance temperature of the stiffened welded hollow spherical joint was proposed.
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